Overview

Dataset statistics

Number of variables17
Number of observations2002
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory266.0 KiB
Average record size in memory136.1 B

Variable types

DateTime1
Numeric14
Categorical2

Alerts

1 is highly overall correlated with 15 and 1 other fieldsHigh correlation
10 is highly overall correlated with 11 and 4 other fieldsHigh correlation
11 is highly overall correlated with 10 and 7 other fieldsHigh correlation
12 is highly overall correlated with 11 and 1 other fieldsHigh correlation
13 is highly overall correlated with 15 and 2 other fieldsHigh correlation
14 is highly overall correlated with 15High correlation
15 is highly overall correlated with 1 and 2 other fieldsHigh correlation
16 is highly overall correlated with 1 and 1 other fieldsHigh correlation
2 is highly overall correlated with 10 and 4 other fieldsHigh correlation
3 is highly overall correlated with 10 and 5 other fieldsHigh correlation
4 is highly overall correlated with 3 and 2 other fieldsHigh correlation
5 is highly overall correlated with 11 and 3 other fieldsHigh correlation
6 is highly overall correlated with 10 and 4 other fieldsHigh correlation
7 is highly overall correlated with 10 and 7 other fieldsHigh correlation
8 is highly overall correlated with 11 and 4 other fieldsHigh correlation
9 is highly overall correlated with 13 and 1 other fieldsHigh correlation
15 is highly imbalanced (66.1%)Imbalance
0 has unique valuesUnique
1 has unique valuesUnique
5 has unique valuesUnique
7 has unique valuesUnique
9 has unique valuesUnique
13 has unique valuesUnique
14 has 1876 (93.7%) zerosZeros

Reproduction

Analysis started2024-05-15 19:00:29.200830
Analysis finished2024-05-15 19:01:26.197397
Duration57 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

0
Date

UNIQUE 

Distinct2002
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
Minimum2015-01-03 01:00:00
Maximum2020-06-26 01:00:00
2024-05-15T12:01:26.418388image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:26.838956image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

1
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2002
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1011.0193
Minimum751.0318
Maximum1327.0633
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:27.265762image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum751.0318
5-th percentile904.55619
Q1965.01122
median1009.5245
Q31055.885
95-th percentile1121.014
Maximum1327.0633
Range576.0315
Interquartile range (IQR)90.873775

Descriptive statistics

Standard deviation68.256084
Coefficient of variation (CV)0.06751215
Kurtosis0.67418081
Mean1011.0193
Median Absolute Deviation (MAD)45.17845
Skewness0.15712071
Sum2024060.6
Variance4658.8931
MonotonicityNot monotonic
2024-05-15T12:01:27.670417image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
970.345 1
 
< 0.1%
1029.8998 1
 
< 0.1%
974.7875 1
 
< 0.1%
986.7204 1
 
< 0.1%
963.4588 1
 
< 0.1%
1038.2351 1
 
< 0.1%
978.4757 1
 
< 0.1%
978.2844 1
 
< 0.1%
1040.2473 1
 
< 0.1%
991.0457 1
 
< 0.1%
Other values (1992) 1992
99.5%
ValueCountFrequency (%)
751.0318 1
< 0.1%
766.4758 1
< 0.1%
777.7424 1
< 0.1%
777.9586 1
< 0.1%
783.3857 1
< 0.1%
791.247 1
< 0.1%
819.676 1
< 0.1%
827.9922 1
< 0.1%
830.4778 1
< 0.1%
835.64 1
< 0.1%
ValueCountFrequency (%)
1327.0633 1
< 0.1%
1292.9535 1
< 0.1%
1284.0224 1
< 0.1%
1261.9023 1
< 0.1%
1257.1058 1
< 0.1%
1242.6811 1
< 0.1%
1239.4978 1
< 0.1%
1224.6558 1
< 0.1%
1221.893 1
< 0.1%
1207.2398 1
< 0.1%

2
Real number (ℝ)

HIGH CORRELATION 

Distinct1971
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.019802
Minimum23.30459
Maximum27.989404
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:28.063792image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum23.30459
5-th percentile24.692354
Q125.507257
median26.102914
Q326.587518
95-th percentile27.161028
Maximum27.989404
Range4.6848145
Interquartile range (IQR)1.0802612

Descriptive statistics

Standard deviation0.76367606
Coefficient of variation (CV)0.029349803
Kurtosis-0.10296193
Mean26.019802
Median Absolute Deviation (MAD)0.53234863
Skewness-0.39347939
Sum52091.644
Variance0.58320113
MonotonicityNot monotonic
2024-05-15T12:01:28.455613image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.63100586 2
 
0.1%
25.84169922 2
 
0.1%
25.87325439 2
 
0.1%
25.97597656 2
 
0.1%
25.84591064 2
 
0.1%
26.10701904 2
 
0.1%
25.90438232 2
 
0.1%
25.50692139 2
 
0.1%
26.24541626 2
 
0.1%
26.1645752 2
 
0.1%
Other values (1961) 1982
99.0%
ValueCountFrequency (%)
23.30458984 1
< 0.1%
23.50570068 1
< 0.1%
23.50969849 1
< 0.1%
23.5854126 1
< 0.1%
23.59307251 1
< 0.1%
23.63308105 1
< 0.1%
23.74416504 1
< 0.1%
23.78597412 1
< 0.1%
23.86593018 1
< 0.1%
23.86721191 1
< 0.1%
ValueCountFrequency (%)
27.9894043 1
< 0.1%
27.97078857 1
< 0.1%
27.94170532 1
< 0.1%
27.76104126 1
< 0.1%
27.7522522 1
< 0.1%
27.74782715 1
< 0.1%
27.7305542 1
< 0.1%
27.72313843 1
< 0.1%
27.70931396 1
< 0.1%
27.67443237 1
< 0.1%

3
Real number (ℝ)

HIGH CORRELATION 

Distinct2000
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.018516326
Minimum0.013458576
Maximum0.021790095
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:28.840461image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.013458576
5-th percentile0.015809142
Q10.017419186
median0.018747094
Q30.019669092
95-th percentile0.020608804
Maximum0.021790095
Range0.008331519
Interquartile range (IQR)0.0022499052

Descriptive statistics

Standard deviation0.0014999646
Coefficient of variation (CV)0.08100768
Kurtosis-0.51238629
Mean0.018516326
Median Absolute Deviation (MAD)0.0010647575
Skewness-0.4708361
Sum37.069685
Variance2.2498938 × 10-6
MonotonicityNot monotonic
2024-05-15T12:01:29.249498image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.019516805 2
 
0.1%
0.019028902 2
 
0.1%
0.018576382 1
 
< 0.1%
0.019165402 1
 
< 0.1%
0.019737571 1
 
< 0.1%
0.019188154 1
 
< 0.1%
0.019424727 1
 
< 0.1%
0.019615397 1
 
< 0.1%
0.018761007 1
 
< 0.1%
0.019409535 1
 
< 0.1%
Other values (1990) 1990
99.4%
ValueCountFrequency (%)
0.013458576 1
< 0.1%
0.013760222 1
< 0.1%
0.014111134 1
< 0.1%
0.014240263 1
< 0.1%
0.014401053 1
< 0.1%
0.014525168 1
< 0.1%
0.014614995 1
< 0.1%
0.014642283 1
< 0.1%
0.014651822 1
< 0.1%
0.01471161 1
< 0.1%
ValueCountFrequency (%)
0.021790095 1
< 0.1%
0.021599382 1
< 0.1%
0.021522835 1
< 0.1%
0.02151547 1
< 0.1%
0.021495502 1
< 0.1%
0.021425324 1
< 0.1%
0.02140834 1
< 0.1%
0.021347908 1
< 0.1%
0.021341497 1
< 0.1%
0.021340372 1
< 0.1%

4
Real number (ℝ)

HIGH CORRELATION 

Distinct1799
Distinct (%)89.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.066169951
Minimum0
Maximum0.40527344
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:29.634367image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0062365532
Q10.023990631
median0.054046631
Q30.093856811
95-th percentile0.16679077
Maximum0.40527344
Range0.40527344
Interquartile range (IQR)0.06986618

Descriptive statistics

Standard deviation0.053714298
Coefficient of variation (CV)0.8117627
Kurtosis2.3888356
Mean0.066169951
Median Absolute Deviation (MAD)0.032291412
Skewness1.3559653
Sum132.47224
Variance0.0028852258
MonotonicityNot monotonic
2024-05-15T12:01:30.058442image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.037719727 5
 
0.2%
0.13641357 4
 
0.2%
0.063079834 4
 
0.2%
0.12805176 3
 
0.1%
0.06890869 3
 
0.1%
0.06741333 3
 
0.1%
0.02355957 3
 
0.1%
0.06411743 3
 
0.1%
0.086761475 3
 
0.1%
0.0501709 3
 
0.1%
Other values (1789) 1968
98.3%
ValueCountFrequency (%)
0 1
< 0.1%
1.835078 × 10-51
< 0.1%
2.11671 × 10-51
< 0.1%
3.3676624 × 10-51
< 0.1%
4.0516257 × 10-51
< 0.1%
6.341934 × 10-51
< 0.1%
0.00010621548 1
< 0.1%
0.00012624264 1
< 0.1%
0.00014030933 1
< 0.1%
0.00014770031 1
< 0.1%
ValueCountFrequency (%)
0.40527344 1
< 0.1%
0.31811523 1
< 0.1%
0.30541992 1
< 0.1%
0.29089355 1
< 0.1%
0.29077148 1
< 0.1%
0.28527832 1
< 0.1%
0.2824707 1
< 0.1%
0.27441406 1
< 0.1%
0.27148438 1
< 0.1%
0.27001953 1
< 0.1%

5
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2002
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.623538
Minimum0.0089788897
Maximum33.65469
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:30.452055image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.0089788897
5-th percentile3.5210975
Q17.4427314
median11.238141
Q317.711405
95-th percentile24.490464
Maximum33.65469
Range33.645711
Interquartile range (IQR)10.268674

Descriptive statistics

Standard deviation6.5880481
Coefficient of variation (CV)0.52188603
Kurtosis-0.57770537
Mean12.623538
Median Absolute Deviation (MAD)4.6640373
Skewness0.48703467
Sum25272.323
Variance43.402378
MonotonicityNot monotonic
2024-05-15T12:01:30.854642image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.85054582 1
 
< 0.1%
8.492288547 1
 
< 0.1%
4.140860069 1
 
< 0.1%
3.786563146 1
 
< 0.1%
9.285719361 1
 
< 0.1%
6.565026578 1
 
< 0.1%
4.643384079 1
 
< 0.1%
10.30994779 1
 
< 0.1%
7.60586761 1
 
< 0.1%
5.362727565 1
 
< 0.1%
Other values (1992) 1992
99.5%
ValueCountFrequency (%)
0.008978889731 1
< 0.1%
0.9167337676 1
< 0.1%
0.9419322793 1
< 0.1%
0.9822894101 1
< 0.1%
0.9993695006 1
< 0.1%
1.016719324 1
< 0.1%
1.052176056 1
< 0.1%
1.080514972 1
< 0.1%
1.105608387 1
< 0.1%
1.138989213 1
< 0.1%
ValueCountFrequency (%)
33.65469013 1
< 0.1%
33.55722238 1
< 0.1%
32.07974197 1
< 0.1%
31.51277294 1
< 0.1%
30.77790244 1
< 0.1%
30.61155931 1
< 0.1%
30.00356558 1
< 0.1%
29.93779923 1
< 0.1%
29.74541372 1
< 0.1%
29.67101691 1
< 0.1%

6
Real number (ℝ)

HIGH CORRELATION 

Distinct1983
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.536313
Minimum20.66485
Maximum27.955713
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:32.102998image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum20.66485
5-th percentile22.433366
Q123.96647
median24.678888
Q325.206934
95-th percentile26.142839
Maximum27.955713
Range7.290863
Interquartile range (IQR)1.2404633

Descriptive statistics

Standard deviation1.1027546
Coefficient of variation (CV)0.044943777
Kurtosis0.86004114
Mean24.536313
Median Absolute Deviation (MAD)0.59754944
Skewness-0.54105737
Sum49121.699
Variance1.2160677
MonotonicityNot monotonic
2024-05-15T12:01:32.526255image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.71932373 2
 
0.1%
24.69875488 2
 
0.1%
24.59230957 2
 
0.1%
24.87130127 2
 
0.1%
24.77218018 2
 
0.1%
24.72536621 2
 
0.1%
25.01473389 2
 
0.1%
24.44411621 2
 
0.1%
25.21529541 2
 
0.1%
24.47860107 2
 
0.1%
Other values (1973) 1982
99.0%
ValueCountFrequency (%)
20.66484985 1
< 0.1%
20.68361816 1
< 0.1%
20.71535645 1
< 0.1%
20.85857544 1
< 0.1%
20.88070068 1
< 0.1%
20.96380005 1
< 0.1%
20.99996338 1
< 0.1%
21.05397949 1
< 0.1%
21.06768188 1
< 0.1%
21.11467896 1
< 0.1%
ValueCountFrequency (%)
27.95571289 1
< 0.1%
27.74901733 1
< 0.1%
27.64394531 1
< 0.1%
27.59749756 1
< 0.1%
27.42446289 1
< 0.1%
27.38125 1
< 0.1%
27.34938965 1
< 0.1%
27.34139404 1
< 0.1%
27.33846436 1
< 0.1%
27.32467041 1
< 0.1%

7
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2002
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0178587
Minimum0.013065504
Maximum0.020951403
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:32.926825image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.013065504
5-th percentile0.015186125
Q10.01667262
median0.01823647
Q30.01900591
95-th percentile0.019815466
Maximum0.020951403
Range0.007885899
Interquartile range (IQR)0.0023332895

Descriptive statistics

Standard deviation0.0014918712
Coefficient of variation (CV)0.083537501
Kurtosis-0.53948835
Mean0.0178587
Median Absolute Deviation (MAD)0.001004326
Skewness-0.54758543
Sum35.753118
Variance2.2256797 × 10-6
MonotonicityNot monotonic
2024-05-15T12:01:33.349648image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.017271755 1
 
< 0.1%
0.01897497 1
 
< 0.1%
0.018074768 1
 
< 0.1%
0.018601244 1
 
< 0.1%
0.018059263 1
 
< 0.1%
0.019081676 1
 
< 0.1%
0.019302724 1
 
< 0.1%
0.018685116 1
 
< 0.1%
0.018982297 1
 
< 0.1%
0.018265096 1
 
< 0.1%
Other values (1992) 1992
99.5%
ValueCountFrequency (%)
0.013065504 1
< 0.1%
0.013332976 1
< 0.1%
0.013536983 1
< 0.1%
0.013645911 1
< 0.1%
0.013673093 1
< 0.1%
0.013676259 1
< 0.1%
0.013854224 1
< 0.1%
0.013857316 1
< 0.1%
0.013878903 1
< 0.1%
0.0138802575 1
< 0.1%
ValueCountFrequency (%)
0.020951403 1
< 0.1%
0.02092876 1
< 0.1%
0.02085963 1
< 0.1%
0.020859309 1
< 0.1%
0.020852108 1
< 0.1%
0.020843904 1
< 0.1%
0.020783335 1
< 0.1%
0.020738358 1
< 0.1%
0.020729717 1
< 0.1%
0.02059998 1
< 0.1%

8
Real number (ℝ)

HIGH CORRELATION 

Distinct1816
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.085145876
Minimum5.3584576 × 10-5
Maximum0.42736816
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:33.782465image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum5.3584576 × 10-5
5-th percentile0.0051080705
Q10.03169632
median0.069152835
Q30.11775971
95-th percentile0.2271698
Maximum0.42736816
Range0.42731458
Interquartile range (IQR)0.086063386

Descriptive statistics

Standard deviation0.070855342
Coefficient of variation (CV)0.83216411
Kurtosis2.8681169
Mean0.085145876
Median Absolute Deviation (MAD)0.041229251
Skewness1.4863764
Sum170.46204
Variance0.0050204795
MonotonicityNot monotonic
2024-05-15T12:01:34.175759image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.12664795 4
 
0.2%
0.051742554 3
 
0.1%
0.06347656 3
 
0.1%
0.053482056 3
 
0.1%
0.0697937 3
 
0.1%
0.08642578 3
 
0.1%
0.15216064 3
 
0.1%
0.0640564 3
 
0.1%
0.094818115 3
 
0.1%
0.033737183 3
 
0.1%
Other values (1806) 1971
98.5%
ValueCountFrequency (%)
5.3584576 × 10-51
< 0.1%
5.9470534 × 10-51
< 0.1%
0.000120550394 1
< 0.1%
0.00029027462 1
< 0.1%
0.0003349781 1
< 0.1%
0.00035512447 1
< 0.1%
0.00036036968 1
< 0.1%
0.00042426586 1
< 0.1%
0.00048804283 1
< 0.1%
0.00052690506 1
< 0.1%
ValueCountFrequency (%)
0.42736816 1
< 0.1%
0.4227295 1
< 0.1%
0.42077637 1
< 0.1%
0.41540527 1
< 0.1%
0.4071045 1
< 0.1%
0.39819336 1
< 0.1%
0.38916016 1
< 0.1%
0.3881836 1
< 0.1%
0.38720703 1
< 0.1%
0.38598633 1
< 0.1%

9
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2002
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8644742
Minimum0.31339551
Maximum19.095462
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:34.572213image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.31339551
5-th percentile2.3403832
Q13.7202672
median5.0414314
Q37.2131408
95-th percentile12.409258
Maximum19.095462
Range18.782067
Interquartile range (IQR)3.4928735

Descriptive statistics

Standard deviation3.0564173
Coefficient of variation (CV)0.52117499
Kurtosis1.2639458
Mean5.8644742
Median Absolute Deviation (MAD)1.6057529
Skewness1.2039218
Sum11740.677
Variance9.3416869
MonotonicityNot monotonic
2024-05-15T12:01:34.990066image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.32894873 1
 
< 0.1%
3.797464554 1
 
< 0.1%
3.637792438 1
 
< 0.1%
2.333239939 1
 
< 0.1%
2.864444599 1
 
< 0.1%
5.458621173 1
 
< 0.1%
5.402560867 1
 
< 0.1%
4.538598689 1
 
< 0.1%
6.200078296 1
 
< 0.1%
3.526802957 1
 
< 0.1%
Other values (1992) 1992
99.5%
ValueCountFrequency (%)
0.3133955097 1
< 0.1%
0.3940930507 1
< 0.1%
0.5393900448 1
< 0.1%
0.8603910869 1
< 0.1%
0.8913131294 1
< 0.1%
0.9268291964 1
< 0.1%
0.935990952 1
< 0.1%
1.045690738 1
< 0.1%
1.059245811 1
< 0.1%
1.142428701 1
< 0.1%
ValueCountFrequency (%)
19.0954621 1
< 0.1%
18.15774946 1
< 0.1%
18.06919143 1
< 0.1%
17.77663675 1
< 0.1%
17.44643987 1
< 0.1%
16.63827168 1
< 0.1%
16.50801092 1
< 0.1%
16.49687917 1
< 0.1%
16.19061465 1
< 0.1%
16.11799772 1
< 0.1%

10
Real number (ℝ)

HIGH CORRELATION 

Distinct1975
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.860317
Minimum20.270044
Maximum25.0953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:35.384674image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum20.270044
5-th percentile21.590004
Q122.374834
median22.897897
Q323.381868
95-th percentile24.033702
Maximum25.0953
Range4.8252563
Interquartile range (IQR)1.0070343

Descriptive statistics

Standard deviation0.74105862
Coefficient of variation (CV)0.032416812
Kurtosis0.012729327
Mean22.860317
Median Absolute Deviation (MAD)0.49919128
Skewness-0.25617507
Sum45766.355
Variance0.54916787
MonotonicityNot monotonic
2024-05-15T12:01:35.774317image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.39156494 2
 
0.1%
22.45302734 2
 
0.1%
23.05404053 2
 
0.1%
22.54683838 2
 
0.1%
23.22237549 2
 
0.1%
23.15368042 2
 
0.1%
23.36776123 2
 
0.1%
23.43569336 2
 
0.1%
23.28310547 2
 
0.1%
22.31191406 2
 
0.1%
Other values (1965) 1982
99.0%
ValueCountFrequency (%)
20.27004395 1
< 0.1%
20.29607544 1
< 0.1%
20.51848755 1
< 0.1%
20.5185791 1
< 0.1%
20.53203735 1
< 0.1%
20.54335938 1
< 0.1%
20.63152466 1
< 0.1%
20.63674316 1
< 0.1%
20.66195068 1
< 0.1%
20.68798218 1
< 0.1%
ValueCountFrequency (%)
25.09530029 1
< 0.1%
24.89321289 1
< 0.1%
24.8098999 1
< 0.1%
24.73696289 1
< 0.1%
24.61428223 1
< 0.1%
24.60592041 1
< 0.1%
24.58947144 1
< 0.1%
24.58251343 1
< 0.1%
24.54003296 1
< 0.1%
24.53371582 1
< 0.1%

11
Real number (ℝ)

HIGH CORRELATION 

Distinct2001
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.016994771
Minimum0.013184203
Maximum0.02008906
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:36.154402image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.013184203
5-th percentile0.0147232
Q10.01602268
median0.017266568
Q30.017953311
95-th percentile0.018718395
Maximum0.02008906
Range0.006904857
Interquartile range (IQR)0.0019306315

Descriptive statistics

Standard deviation0.0012661505
Coefficient of variation (CV)0.074502359
Kurtosis-0.46756215
Mean0.016994771
Median Absolute Deviation (MAD)0.000866522
Skewness-0.50286394
Sum34.023531
Variance1.6031371 × 10-6
MonotonicityNot monotonic
2024-05-15T12:01:36.566448image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.017212441 2
 
0.1%
0.016562222 1
 
< 0.1%
0.018036554 1
 
< 0.1%
0.017090576 1
 
< 0.1%
0.017128771 1
 
< 0.1%
0.016983518 1
 
< 0.1%
0.01765498 1
 
< 0.1%
0.017944692 1
 
< 0.1%
0.017388118 1
 
< 0.1%
0.017486935 1
 
< 0.1%
Other values (1991) 1991
99.5%
ValueCountFrequency (%)
0.013184203 1
< 0.1%
0.013244578 1
< 0.1%
0.013303127 1
< 0.1%
0.013320945 1
< 0.1%
0.013348844 1
< 0.1%
0.013404061 1
< 0.1%
0.013470897 1
< 0.1%
0.01351267 1
< 0.1%
0.013590389 1
< 0.1%
0.01360806 1
< 0.1%
ValueCountFrequency (%)
0.02008906 1
< 0.1%
0.01989226 1
< 0.1%
0.019754171 1
< 0.1%
0.019668505 1
< 0.1%
0.019661602 1
< 0.1%
0.019618059 1
< 0.1%
0.019525422 1
< 0.1%
0.019494249 1
< 0.1%
0.019479508 1
< 0.1%
0.01943304 1
< 0.1%

12
Real number (ℝ)

HIGH CORRELATION 

Distinct1707
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.13610804
Minimum0.001434803
Maximum0.46826172
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:36.985000image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.001434803
5-th percentile0.03720398
Q10.077178955
median0.12187195
Q30.17453003
95-th percentile0.29331055
Maximum0.46826172
Range0.46682692
Interquartile range (IQR)0.097351078

Descriptive statistics

Standard deviation0.078081246
Coefficient of variation (CV)0.57367105
Kurtosis0.75454712
Mean0.13610804
Median Absolute Deviation (MAD)0.048172003
Skewness0.96720533
Sum272.48831
Variance0.0060966809
MonotonicityNot monotonic
2024-05-15T12:01:37.393818image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.17980957 6
 
0.3%
0.068603516 4
 
0.2%
0.17419434 3
 
0.1%
0.1720581 3
 
0.1%
0.10592651 3
 
0.1%
0.13586426 3
 
0.1%
0.13500977 3
 
0.1%
0.101867676 3
 
0.1%
0.15979004 3
 
0.1%
0.14367676 3
 
0.1%
Other values (1697) 1968
98.3%
ValueCountFrequency (%)
0.001434803 1
< 0.1%
0.0018720627 1
< 0.1%
0.0029201508 1
< 0.1%
0.0049591064 1
< 0.1%
0.006254196 1
< 0.1%
0.007200241 1
< 0.1%
0.008144379 1
< 0.1%
0.008926392 1
< 0.1%
0.010784149 1
< 0.1%
0.012622833 1
< 0.1%
ValueCountFrequency (%)
0.46826172 1
< 0.1%
0.4276123 1
< 0.1%
0.4239502 1
< 0.1%
0.41333008 1
< 0.1%
0.4124756 1
< 0.1%
0.40734863 1
< 0.1%
0.40161133 1
< 0.1%
0.39770508 1
< 0.1%
0.397583 1
< 0.1%
0.39624023 1
< 0.1%

13
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2002
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7105462
Minimum0.038669383
Maximum9.9716645
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:37.784196image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.038669383
5-th percentile1.4318678
Q12.6024289
median3.569944
Q34.6458618
95-th percentile6.4188021
Maximum9.9716645
Range9.9329952
Interquartile range (IQR)2.0434329

Descriptive statistics

Standard deviation1.5386157
Coefficient of variation (CV)0.41466016
Kurtosis0.18774012
Mean3.7105462
Median Absolute Deviation (MAD)1.021988
Skewness0.49029491
Sum7428.5134
Variance2.3673382
MonotonicityNot monotonic
2024-05-15T12:01:38.178383image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.364147952 1
 
< 0.1%
3.163074553 1
 
< 0.1%
3.074125226 1
 
< 0.1%
3.014882633 1
 
< 0.1%
2.028136875 1
 
< 0.1%
3.12123159 1
 
< 0.1%
4.008375847 1
 
< 0.1%
2.556075466 1
 
< 0.1%
4.34382358 1
 
< 0.1%
1.503705533 1
 
< 0.1%
Other values (1992) 1992
99.5%
ValueCountFrequency (%)
0.0386693829 1
< 0.1%
0.1035752289 1
< 0.1%
0.135350314 1
< 0.1%
0.1568605677 1
< 0.1%
0.1653773399 1
< 0.1%
0.2522155039 1
< 0.1%
0.2707413114 1
< 0.1%
0.3216698754 1
< 0.1%
0.3684209402 1
< 0.1%
0.4303616081 1
< 0.1%
ValueCountFrequency (%)
9.971664548 1
< 0.1%
9.112237206 1
< 0.1%
9.03474996 1
< 0.1%
8.967193741 1
< 0.1%
8.845326124 1
< 0.1%
8.750118721 1
< 0.1%
8.564446742 1
< 0.1%
8.5484231 1
< 0.1%
8.44157348 1
< 0.1%
8.400210936 1
< 0.1%

14
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct23
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7047952
Minimum0
Maximum22
Zeros1876
Zeros (%)93.7%
Negative0
Negative (%)0.0%
Memory size15.8 KiB
2024-05-15T12:01:38.524941image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum22
Range22
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1482235
Coefficient of variation (CV)4.4668629
Kurtosis24.080743
Mean0.7047952
Median Absolute Deviation (MAD)0
Skewness4.8968191
Sum1411
Variance9.9113113
MonotonicityNot monotonic
2024-05-15T12:01:38.832116image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 1876
93.7%
12 7
 
0.3%
3 6
 
0.3%
11 6
 
0.3%
21 6
 
0.3%
19 6
 
0.3%
16 6
 
0.3%
4 6
 
0.3%
2 6
 
0.3%
1 6
 
0.3%
Other values (13) 71
 
3.5%
ValueCountFrequency (%)
0 1876
93.7%
1 6
 
0.3%
2 6
 
0.3%
3 6
 
0.3%
4 6
 
0.3%
5 6
 
0.3%
6 6
 
0.3%
7 6
 
0.3%
8 6
 
0.3%
9 6
 
0.3%
ValueCountFrequency (%)
22 5
0.2%
21 6
0.3%
20 5
0.2%
19 6
0.3%
18 5
0.2%
17 5
0.2%
16 6
0.3%
15 5
0.2%
14 5
0.2%
13 5
0.2%

15
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
0
1876 
1
 
126

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2002
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1876
93.7%
1 126
 
6.3%

Length

2024-05-15T12:01:39.165480image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T12:01:39.433748image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
0 1876
93.7%
1 126
 
6.3%

Most occurring characters

ValueCountFrequency (%)
0 1876
93.7%
1 126
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2002
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1876
93.7%
1 126
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2002
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1876
93.7%
1 126
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1876
93.7%
1 126
 
6.3%

16
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.8 KiB
1
1457 
0
545 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2002
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1 1457
72.8%
0 545
 
27.2%

Length

2024-05-15T12:01:39.731852image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-15T12:01:39.998624image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
1 1457
72.8%
0 545
 
27.2%

Most occurring characters

ValueCountFrequency (%)
1 1457
72.8%
0 545
 
27.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2002
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1457
72.8%
0 545
 
27.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2002
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1457
72.8%
0 545
 
27.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1457
72.8%
0 545
 
27.2%

Interactions

2024-05-15T12:01:21.621884image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:31.261514image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:35.054584image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:38.993981image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:42.722791image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:46.718382image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:50.541488image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:55.190125image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:59.138577image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:02.748745image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:06.637345image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:10.323931image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:14.312310image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:17.970721image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:21.857626image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:31.559506image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:35.304890image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:39.243988image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:42.997642image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:46.994289image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:50.807636image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:55.455731image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:59.388691image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:03.015533image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:06.903291image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:10.611327image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:14.563081image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:18.224375image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:22.095506image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:31.802649image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:35.633020image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:39.494238image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:43.263389image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:47.260345image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:51.082582image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:55.721352image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:59.623373image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:03.291384image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:07.138932image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:10.911968image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:14.813076image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:18.482070image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:22.331975image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:32.061769image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:35.954312image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:39.744361image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:43.544622image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:47.526009image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:51.348967image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:55.971353image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:59.873808image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:03.542634image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:07.382952image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:11.161958image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:15.063097image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:18.732091image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:22.608325image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:32.352168image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:36.314394image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:40.051536image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:43.842220image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:47.807509image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:51.661994image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:56.296196image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:00.164240image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:03.823610image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:07.696558image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:11.484298image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:15.353228image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:18.998045image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:22.877101image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:32.618155image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:36.642530image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:40.317714image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:44.132159image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:48.098145image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:51.943496image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:56.576232image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:00.445763image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:04.136699image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:07.947179image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:11.781455image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:15.619230image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:19.307526image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:23.146281image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:32.909029image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:36.932283image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:40.598978image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:44.444786image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:48.380105image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:52.234970image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:56.875474image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:00.696848image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:04.414717image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:08.237278image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:12.078738image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:15.901071image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:19.578067image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:23.422341image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:33.211135image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:37.229409image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:40.873542image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:44.757874image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:48.681857image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:52.532093image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:57.211551image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:00.983819image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:04.734200image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:08.518388image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:12.385451image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:16.183139image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:19.874982image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:23.675591image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:33.456632image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:37.464337image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:41.117131image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:45.032874image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:48.916301image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:52.782106image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:57.477313image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:01.237896image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:04.991030image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:08.753797image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:12.635978image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:16.427146image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:20.125403image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:23.957839image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:33.753509image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:37.745659image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:41.415011image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:45.330124image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:49.217051image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:53.888983image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:57.791068image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:01.519905image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:05.297976image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:09.054446image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:12.964813image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:16.708396image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:20.412533image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:24.193965image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:33.997314image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:37.983449image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:41.665544image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:45.611883image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:49.467045image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:54.140086image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:58.073149image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:01.754254image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:05.547563image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:09.296000image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:13.214852image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:16.959623image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:20.649764image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:24.470556image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:34.282353image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:38.265021image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:41.955760image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:45.912363image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:49.770349image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:54.430027image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:58.363909image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:02.035525image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:05.844956image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:09.577375image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:13.521108image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:17.242389image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:20.907046image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:24.722897image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:34.545070image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:38.499809image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:42.206788image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:46.185003image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:50.024078image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:54.680030image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:58.629533image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:02.279052image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:06.095906image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:09.829323image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:13.786728image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:17.500731image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:21.156689image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:24.958640image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:34.796139image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:38.750450image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:42.472435image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:46.451521image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:50.290986image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:54.945634image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:00:58.879524image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:02.515733image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:06.387014image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:10.065792image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:14.052367image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:17.735532image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-05-15T12:01:21.387403image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-05-15T12:01:40.248841image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
11011121314151623456789
11.0000.1910.084-0.125-0.029-0.0771.0001.0000.1770.088-0.1470.1170.1750.082-0.1250.011
100.1911.0000.7840.275-0.254-0.0630.0000.0000.7700.6210.269-0.2400.8300.6970.290-0.298
110.0840.7841.0000.537-0.249-0.1100.0220.0220.7540.8240.496-0.6010.6300.9340.591-0.444
12-0.1250.2750.5371.000-0.055-0.0270.0000.0000.1950.3350.426-0.4180.1810.4840.718-0.174
13-0.029-0.254-0.249-0.0551.0000.0721.0001.000-0.323-0.348-0.0990.302-0.210-0.261-0.0830.776
14-0.077-0.063-0.110-0.0270.0721.0000.9950.283-0.077-0.107-0.0540.119-0.062-0.121-0.0700.107
151.0000.0000.0220.0001.0000.9951.0000.105-0.080-0.111-0.0580.123-0.062-0.126-0.0740.111
161.0000.0000.0220.0001.0000.2830.1051.0000.4650.3600.365-0.3250.4490.3960.318-0.272
20.1770.7700.7540.195-0.323-0.077-0.0800.4651.0000.7650.416-0.4120.7610.7610.346-0.409
30.0880.6210.8240.335-0.348-0.107-0.1110.3600.7651.0000.604-0.4830.5250.8520.471-0.472
4-0.1470.2690.4960.426-0.099-0.054-0.0580.3650.4160.6041.000-0.4490.2710.5250.617-0.233
50.117-0.240-0.601-0.4180.3020.1190.123-0.325-0.412-0.483-0.4491.000-0.187-0.624-0.5570.540
60.1750.8300.6300.181-0.210-0.062-0.0620.4490.7610.5250.271-0.1871.0000.6380.319-0.248
70.0820.6970.9340.484-0.261-0.121-0.1260.3960.7610.8520.525-0.6240.6381.0000.644-0.437
8-0.1250.2900.5910.718-0.083-0.070-0.0740.3180.3460.4710.617-0.5570.3190.6441.000-0.259
90.011-0.298-0.444-0.1740.7760.1070.111-0.272-0.409-0.472-0.2330.540-0.248-0.437-0.2591.000

Missing values

2024-05-15T12:01:25.320664image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-15T12:01:25.928460image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

012345678910111213141516
02015-01-03 01:00:00970.34525.8652590.0185760.01617421.85054623.4824460.0172720.00185510.32894922.6621340.0165620.09615.364148000
12015-01-04 01:00:00944.055625.6818180.0184940.00389819.8933523.627130.017540.0064818.28743322.533380.0167470.0855714.433089000
22015-01-05 01:00:00928.533825.6899050.0184230.01811220.81284323.5102170.016660.00776311.8194722.4008420.0159130.0820626.599681000
32015-01-06 01:00:00914.689525.4410340.0176280.02403328.39983223.6050960.016590.00887714.2224122.2847840.0158350.0881047.670477000
42015-01-07 01:00:00940.456824.8632450.0169430.01515620.15655422.4257450.0163860.01540410.07821721.7616820.0155730.1002816.593827000
52015-01-08 01:00:00962.406825.0508060.0176030.02162219.64667122.5429930.0163670.0327159.83693321.5976810.0157490.1276256.068857000
62015-01-09 01:00:00943.608125.0384770.0166460.02394126.21308822.9759770.0155780.02117213.29401422.1947270.0154110.0962526.865419210
72015-01-10 01:00:00906.95824.9764950.0172150.02525321.33533323.554620.0164210.05137612.48562722.2889950.0157350.1218266.229961000
82015-01-11 01:00:00924.279525.1690610.0182490.02240820.80437923.5362490.0167080.02663411.4822422.4424990.0158310.098456.030867000
92015-01-12 01:00:00941.546925.299890.0185680.03390520.03641823.831140.0172710.0242778.45808523.049890.0162790.0937813.699248000
012345678910111213141516
19922020-06-17 01:00:001061.095926.8621770.0198750.02465111.52827625.0028020.0192730.0296486.36684623.3934270.0184870.1000674.535985001
19932020-06-18 01:00:001005.427826.9858640.020760.1668710.36817724.8764890.0189220.0635993.40427823.4546140.0178380.0924382.195117001
19942020-06-19 01:00:001043.996826.6758670.0195020.01898211.12851725.3789920.0196550.184574.03626123.3321170.018350.1846923.542784001
19952020-06-20 01:00:001029.15226.7284480.0205040.1186227.80515325.1815730.0194430.1661994.85144323.8846980.0191380.0654915.003853001
19962020-06-21 01:00:001028.962226.7691280.0204870.0845959.54916824.7222530.0188390.0465093.38389222.5660030.0172210.0364993.044263001
19972020-06-22 01:00:001027.854726.5270940.0199060.0702827.03772824.1989690.0180830.0321352.84684322.4958440.0171290.0411832.46788001
19982020-06-23 01:00:001078.387427.2314090.0207530.0792249.56450925.9345340.0200360.1051034.05618423.9814090.0190370.1742553.698103001
19992020-06-24 01:00:00965.27226.7523440.0203710.0800487.16046325.3773440.0196770.0841674.28339423.4710940.0185250.0928963.727516001
20002020-06-25 01:00:001060.007526.9594970.020860.03889510.75626524.9907470.0190130.0594942.44618923.0844970.0178760.1206362.878472001
20012020-06-26 01:00:001068.253226.7840820.0202720.04667714.93714824.9715820.0189750.0863953.19637823.2215820.0179910.179262.732777001